Correlation b/w dependent vars.(food loss and food waste)
## # A tibble: 3 × 4
## rowname food_waste_kg liquid_waste_kg solid_waste_kg
## * <chr> <dbl> <dbl> <dbl>
## 1 food_waste_kg 1 0.97 0.88
## 2 liquid_waste_kg 0.97 1 0.73
## 3 solid_waste_kg 0.88 0.73 1
## food_waste_kg liquid_waste_kg solid_waste_kg
## food_waste_kg 0.000000e+00 9.849303e-100 5.265564e-52
## liquid_waste_kg 9.849303e-100 0.000000e+00 2.938486e-28
## solid_waste_kg 5.265564e-52 2.938486e-28 0.000000e+00
Correlation b/w dependent vars.(food loss and food waste)
## # A tibble: 3 × 4
## rowname food_waste_kg liquid_waste_kg solid_waste_kg
## * <chr> <dbl> <dbl> <dbl>
## 1 food_waste_kg NaN NaN NaN
## 2 liquid_waste_kg NaN NaN NaN
## 3 solid_waste_kg NaN NaN NaN
## food_waste_kg liquid_waste_kg solid_waste_kg
## food_waste_kg 0 NaN NaN
## liquid_waste_kg NaN 0 NaN
## solid_waste_kg NaN NaN 0
Correlation b/w independent vars.
## # A tibble: 9 × 10
## rowname food_waste_kg solid_waste_kg liquid_waste_kg halfs liquors sales
## * <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 food_waste_… 1 0.88 0.97 0.47 0.28 0.69
## 2 solid_waste… 0.88 1 0.73 0.34 0.29 0.58
## 3 liquid_wast… 0.97 0.73 1 0.49 0.26 0.68
## 4 halfs 0.47 0.34 0.49 1 0.15 0.5
## 5 liquors 0.28 0.29 0.26 0.15 1 0.46
## 6 sales 0.69 0.58 0.68 0.5 0.46 1
## 7 temp_c 0.18 0.12 0.2 0.094 0.066 0.27
## 8 humi_p -0.068 -0.071 -0.06 -0.15 -0.23 -0.11
## 9 prcp_mm -0.16 -0.16 -0.14 -0.097 -0.18 -0.16
## # ℹ 3 more variables: temp_c <dbl>, humi_p <dbl>, prcp_mm <dbl>
## food_waste_kg solid_waste_kg liquid_waste_kg halfs liquors
## food_waste_kg 0.0000 0.0000 0.0000 0.0000 0.0003
## solid_waste_kg 0.0000 0.0000 0.0000 0.0000 0.0002
## liquid_waste_kg 0.0000 0.0000 0.0000 0.0000 0.0011
## halfs 0.0000 0.0000 0.0000 0.0000 0.0579
## liquors 0.0003 0.0002 0.0011 0.0579 0.0000
## sales 0.0000 0.0000 0.0000 0.0000 0.0000
## temp_c 0.0193 0.1374 0.0107 0.2362 0.4023
## humi_p 0.3904 0.3714 0.4462 0.0528 0.0028
## prcp_mm 0.0459 0.0462 0.0701 0.2214 0.0247
## sales temp_c humi_p prcp_mm
## food_waste_kg 0.0000 0.0193 0.3904 0.0459
## solid_waste_kg 0.0000 0.1374 0.3714 0.0462
## liquid_waste_kg 0.0000 0.0107 0.4462 0.0701
## halfs 0.0000 0.2362 0.0528 0.2214
## liquors 0.0000 0.4023 0.0028 0.0247
## sales 0.0000 0.0006 0.1738 0.0445
## temp_c 0.0006 0.0000 0.2340 0.6566
## humi_p 0.1738 0.2340 0.0000 0.0000
## prcp_mm 0.0445 0.6566 0.0000 0.0000
Correlation b/w independent vars.
## # A tibble: 6 × 7
## rowname temp_c humi_p prcp_mm customers liquors sales
## * <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 temp_c 1 0.094 -0.035 0.24 0.066 0.27
## 2 humi_p 0.094 1 0.35 -0.065 -0.23 -0.11
## 3 prcp_mm -0.035 0.35 1 -0.16 -0.18 -0.16
## 4 customers 0.24 -0.065 -0.16 1 0.32 0.84
## 5 liquors 0.066 -0.23 -0.18 0.32 1 0.46
## 6 sales 0.27 -0.11 -0.16 0.84 0.46 1
## temp_c humi_p prcp_mm customers liquors
## temp_c 0.000000000 2.340014e-01 6.565817e-01 2.439128e-03 4.022764e-01
## humi_p 0.234001450 0.000000e+00 5.743318e-06 4.097823e-01 2.795016e-03
## prcp_mm 0.656581713 5.743318e-06 0.000000e+00 3.857002e-02 2.466598e-02
## customers 0.002439128 4.097823e-01 3.857002e-02 0.000000e+00 3.121698e-05
## liquors 0.402276407 2.795016e-03 2.466598e-02 3.121698e-05 0.000000e+00
## sales 0.000633642 1.738069e-01 4.451900e-02 1.320143e-44 5.456896e-10
## sales
## temp_c 6.336420e-04
## humi_p 1.738069e-01
## prcp_mm 4.451900e-02
## customers 1.320143e-44
## liquors 5.456896e-10
## sales 0.000000e+00
## Correlation computed with
## • Method: 'pearson'
## • Missing treated using: 'pairwise.complete.obs'
Correlogram
Cross-Correlation
